Using Fuzzy Logic to Make Decisions Based on the Data From Customer Relationship Management Systems
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1
Faculty of Management, Department of Marketing, Lublin University of Technology, ul. Nadbystrzycka 38, 20-618 Lublin, Poland
2
Faculty of Management, Department of Organization of Enterprise,
Lublin University of Technology, ul. Nadbystrzycka 38, 20-618 Lublin, Poland
Corresponding author
Agnieszka Barbara Bojanowska
Faculty of Management, Department of Marketing, Lublin University of Technology, ul. Nadbystrzycka 38, 20-618 Lublin, Poland
Adv. Sci. Technol. Res. J. 2023; 17(5):269-279
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ABSTRACT
The purpose of the article is to propose a fuzzy logic solution for decision-making based on data from CRM (Customer Relationship Management) systems to evaluate banking customer attractiveness. The article is based on theory about management IT systems, especially the CRM type. Based on the literature research, nine identified factors were proposed that can influence whether the relationship with the customer will be profitable for the bank. Factors that affect banking customer attractiveness are considered, including the share of the customer's wallet and the customer's tendency to express a positive opinion of the bank. Data allowing for the identification of these factors is collected in the bank's IT systems, among other CRMs. Based on the research, a model prepared in Simulink using a Mamdani-type Fuzzy Inference System was made. It is a decision model that provides a result in the form of a binary value of 0 or 1, where 1 means it is worth investing in a customer, while 0 means it is not. After considering the subjective opinions, competence and experience of specialists and confronting them with the results from the developed model, it can be confirmed that the model works as expected.